On Mon, Aug 10, 2020 at 8:37 PM Sebastian Berg <[email protected]> wrote:
> On Mon, 2020-08-10 at 17:35 +0200, Hameer Abbasi wrote: > > Hi, > > > > We should have a higher-bandwidth meeting/communication for all > > stakeholders, and particularly some library authors, to see what > > would be good for them. > I'm not sure that helps. At this point there's little progress since the last meeting, I think the plan is unchanged: we need implementations of all the options on offer, and then try them out in PRs for scikit-learn, SciPy and perhaps another package who's maintainers are interested, to test like=, __array_module__ in realistic situations. > > > We should definitely have language in the NEP that says it won’t be > > in a release unless the NEP is accepted. > > In that case, I think the important part is to have language right now > in the implementation, although that can refer to the NEP itself of > course. > You can't expect everyone who may be tempted to use it to actually read > the NEP draft, at least not without pointing it out. > Agreed, I think the decision is on this list not in the NEP, and to make sure we won't forget we need an issue opened with the 1.20 milestone. Cheers, Ralf > I will say that I think it is not very high risk, because I think > annoying or not, the argument could be deprecated again with a > transition short phase. Admittedly, that argument only works if we have > a replacement solution. > > Cheers, > > Sebastian > > > > > > Best regards, > > Hameer Abbasi > > > > -- > > Sent from Canary (https://canarymail.io) > > > > > On Monday, Aug 10, 2020 at 5:31 PM, Sebastian Berg < > > > [email protected] (mailto:[email protected])> > > > wrote: > > > Hi all, > > > > > > as a heads up that Peter Entschev has a PR open to add `like=` to > > > most array creation functions, my current plan is to merge it soon > > > as a preliminary API and bring it up again before the actual > > > release (in a few months). This allows overriding for array-likes, > > > e.g. it will allow: > > > > > > > > > arr = np.asarray([3], like=dask_array) > > > type(arr) is dask.array.Array > > > > > > This was proposed in NEP 35: > > > > > > > https://numpy.org/neps/nep-0035-array-creation-dispatch-with-array-function.html > > > > > > Although that has not been accepted as of now, the PR is: > > > > > > https://github.com/numpy/numpy/pull/16935 > > > > > > > > > This was discussed in a smaller group, and is an attempt to see how > > > we > > > can make the array-function protocol viable to allow packages such > > > as > > > sklearn to work with non-NumPy arrays. > > > > > > As of now, this would be experimental and can revisit it before the > > > actual NumPy release. We should probably discuss accepting NEP 35 > > > more. At this time, I hope that we can put in the functionality to > > > facilitate this discussion, rather the other way around. > > > > > > If anyone feels nervous about this step, I would be happy to > > > document > > > that we will not include it in the next release unless the NEP is > > > accepted first, or at least hide it behind an environment variable. > > > > > > Cheers, > > > > > > Sebastian > > > > > > _______________________________________________ > > > NumPy-Discussion mailing list > > > [email protected] > > > https://mail.python.org/mailman/listinfo/numpy-discussion > > > > _______________________________________________ > > NumPy-Discussion mailing list > > [email protected] > > https://mail.python.org/mailman/listinfo/numpy-discussion > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > https://mail.python.org/mailman/listinfo/numpy-discussion >
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